This paper presents and designs a monitoring and early warning system for automated container terminals based on UAV inspecting. Developed on the Raspberry Pi platform

the system leverages computer vision-based object detection technologies to achieve multiple functions including multi-target detection in terminals

identification of container damage

and recognition of irregular stacking areas. In terms of drone structural design

stress verification of critical components has been completed. The system emphasizes the establishment of a visual perception system integrated with image processing algorithms. Python-based modules for multi-target detection and container damage identification have been developed

complemented by a graphical user interface that visually displays perception results. Addressing current deficiencies in automated terminal monitoring

this system provides a novel approach for intelligent construction in container terminal operations.